is median a chafractoristic of population
The mode is the most probable value. Often, you determine the mode by plotting the experimental probability distribution, and finding the peak value. The mode is not necessarily the same as the mean nor the median, unless the distribution is symmetrical.
The answer depends on the probability distribution of WHAT variable. The variable could be the sum or the product of the three numbers, the maximum, minimum, the mean, median, number of 3s, number of primes, and so on.
The formula is: median of lognormal = exp(u)
If you will let me assume that the probability density function (pdf) is absolutely continuous over its support then the median is given as the integral from -inf to the median of the pdf over that support = 1/2.
yes
You integrate the probability distribution function to get the cumulative distribution function (cdf). Then find the value of the random variable for which cdf = 0.5.
is median a chafractoristic of population
a discrete probability distribution, a median m satisfies the inequalitiesorin which a Lebesgue-Stieltjes integral is used. For an absolutely continuous probability distribution with probability density function ƒ, we have[edit]Medians of particular distributionsThe medians of certain types of distributions can be easily calculated from their parameters:The median of a normal distribution with mean μ and variance σ2 is μ. In fact, for a normal distribution, mean = median = mode.The median of a uniform distribution in the interval [a, b] is (a + b) / 2, which is also the mean.The median of a Cauchy distribution with location parameter x0 and scale parameter y is x0, the location parameter.The median of an exponential distribution with rate parameter λ is the natural logarithm of 2 divided by the rate parameter: λ−1ln 2.The median of a Weibull distribution with shape parameter k and scale parameter λ is λ(ln 2)1/k.
If the data is ordered, that would be the median. If organised according to probability, that would be the mean.
The mode is the most probable value. Often, you determine the mode by plotting the experimental probability distribution, and finding the peak value. The mode is not necessarily the same as the mean nor the median, unless the distribution is symmetrical.
The answer depends on the probability distribution of WHAT variable. The variable could be the sum or the product of the three numbers, the maximum, minimum, the mean, median, number of 3s, number of primes, and so on.
The formula is: median of lognormal = exp(u)
If you will let me assume that the probability density function (pdf) is absolutely continuous over its support then the median is given as the integral from -inf to the median of the pdf over that support = 1/2.
The median is defined as the middle value in a set or distribution. There is no arithmetic involved in finding the median unless the set or distribution has an even number of values, in which case the the two middle values (sometimes defined as lower median and upper median) are averaged to find the median.
You cannot because the median of a distribution is not related to its standard deviation.
They are probability distributions!